Comparison of Traditional and New Anthropometric Indices in Children and Adolescents Whose Body Fat Percentage Analysis was Performed with Bioelectrical Impedance Analysis

Yıl 2024, Cilt: 8 Sayı: 1, 79 - 87, 29.04.2024

Yavuz Özer Didem Güneş Kaya

https://doi.org/10.25048/tudod.1419220

Öz

Aim: The aim of this study is to investigate the predictive ability efficiency of body mass index (BMI), waist circumference, hip
circumference, waist-to-height ratio, triponderal mass index (TMI), body adiposity index (BAI), pediatric body adiposity index (BAIp),
body shape index (ABSI-adolescent), body roundness index (BRI), abdominal volume index (AVI), and conicity index (CI) in forecasting
overweight/obesity and predicting percentage of body fat (PBF) in children and adolescents.
Material and Methods: Children and adolescents aged 6-18 without chronic illnesses were included in the study. To assess body
composition, bioelectrical impedance analysis (BIA) was employed as the reference method, and the cases were categorized into two
groups: the lean/normal (Group 1) and overweight/obese (Group 2) groups. The evaluation of the data involved the use of descriptive
statistics, independent t-test, Mann-Whitney U test, and Receiver Operating Characteristic (ROC) analysis.
Results: A total of 466 cases (58.6% female, 41.4% male) were included in the study. The median age of the cases was 13.2 (10.1-
16.0) years. According to BIA, 10.7% of the cases (n=50) were classified as underweight, 33.7% (n=157) as normal weight, 10.9%
(n=51) as overweight, and 44.6% (n=208) as obese. Overweight/obese individuals exhibited significantly higher values for BMI-SDS,
waist circumference, hip circumference, waist-to-height ratio, TMI, BAI, BAIp, ABSI-adolescent, BRI, AVI, and CI (p<0.05). When
referencing bioelectrical impedance analysis, BAIp [area under the curve (AUC) =0.980, 95% confidence interval (CI)=0.959-1.000,
p=0.010], BMI-SDS (AUC=0.968, 95% CI=0.948-1.000, p=0.004), waist circumference (AUC=0.968, 95% CI=0.947-0.990, p=0.011),
hip circumference (AUC=0.967, 95% CI=0.943-0.991, p=0.012), waist-to-height ratio (AUC=0.968, 9%5 CI=0.946-0.990, p=0.011),
TMI (AUC=0.968, 95% CI=0.947-1.000, p=0.007), BRI (AUC=0.968, 95% CI=0.947-0.990, p=0.011), and AVI (AUC=0.969, 95%
CI=0.948-0.990, p=0.011) demonstrated excellent performance in distinguishing overweight/obesity. Body adiposity index showed
good performance (AUC=0.888, 95% CI=0.842-0.934, p=0.024), ABSI-adolescent (AUC=0.745, 95% CI=0.656-0.798, p=0.036), and CI
showed poor performance (AUC=0.627, 95% CI=0.555-0.714, p=0.041).
Conclusion: In children and adolescents, BAIp, BMI-SDS, waist circumference, hip circumference, waist-to-height ratio, TMI, BRI, and
AVI can be utilized to predict PBF and assess overweight/obesity.

Anahtar Kelimeler

Children, adolescent, anthropometry, body composition, percentage of body fat

Biyoelektrik İmpedans Analiz ile Vücut Yağı Yüzdesi Analizi Yapılan Çocuk ve Adölesanlarda Geleneksel ve Yeni Antropometrik İndekslerin Karşılaştırılması

Öz

Amaç: Bu çalışmanın amacı, çocuk ve adölesanlarda beden kütle indeksi (BKİ), bel çevresi, kalça çevresi, bel/boy oranı, triponderal
kütle indeksi (TKİ), beden adipozite indeksi (BAİ), pediatrik beden adipozite indeksi (BAİp), beden şekil indeksi (ABSI-adölesan),
beden yuvarlaklık indeksi (BRI), abdominal volüm indeksi (AVİ) ve konisite indeksinin (Kİ) fazla kilolu/obeziteyi tahmin etme ve
beden yağı yüzdesini (PBF) öngörme etkinliğinin araştırılmasıdır.
Gereç ve Yöntemler: Kronik hastalığı olmayan 6-18 yaş arasındaki çocuk ve adölesanlar dahil edildi. Vücut kompozisyonunu
değerlendirmek için biyoelektrik impedans analizi (BİA) referans yöntem kullanılarak olgular zayıf/normal (grup 1) ve fazla kilolu/
obez (grup 2) olmak üzere 2 gruba ayrıldı. Verilerin değerlendirilmesinde tanımlayıcı istatistikler ile bağımsız t-testi, Mann-Whitney U
ve İşlem Karakteristiği Eğrisi (ROC) analizi kullanıldı.
Bulgular: Çalışmaya toplamda 466 olgu (%58,6 kız, %41,4 erkek) dahil edildi. Katılımcıların ortanca yaşı 13,2 (10,1-16,0) idi. BİA’ya
göre olguların %10,7’si (n=50) zayıf, %33,7’u (n=157) normal, %10,9’u (n=51) fazla kilolu iken %44,6’ü (n=208) obez idi. Tüm kohortta,
fazla kilolu/obezlerde BKİ-SDS, bel çevresi, kalça çevresi, bel/boy oranı, TKİ, BAİ, BAİp, ABSI-adölesan, BRI, AVİ ve Kİ anlamlı olarak
yüksekti (p<0,05). Biyoelektrik impedans analizi referans alındığında, fazla kilolu/obeziteyi ayırt etmede, BAİp [eğri altında kalan alan
(area under the curve=AUC) =0,980, %95 güven aralığı (GA)=0,959-1,000, p=0,010], BKİ-SDS (AUC=0,968, %95 GA=0,948-1,000,
p=0,004), bel çevresi (AUC=0,968, %95 GA=0,947-0,990, p=0,011), kalça çevresi (AUC=0,967, %95 GA=0,943-0,991, p=0,012), bel/
boy oranı (AUC=0,968, %95 GA=0,946-0,990, p=0,011), TKİ (AUC=0,968, %95 GA=0,947-1,000, p=0,007), BRI (AUC=0,968, %95
GA=0,947-0,990, p=0,011) ve AVİ (AUC=0,969, %95 GA=0,948-0,990, p=0,011) mükemmel performans gösterdi. Beden adiposite
indeksi iyi (AUC=0,888, %95 GA=0,842-0,934, p=0,024), ABSI-adölesan (AUC=0,745, %95 GA=0,656-0,798, p=0,036), Kİ ise zayıf
performans gösterdi (AUC=0,627, %95 GA=0,555-0,714, p=0,041).
Sonuç: Çocuk ve adölesanlarda, PBF’yi tahmin etmek ve fazla kilolu/obeziteyi değerlendirmek için BAİp, BKİ-SDS, bel çevresi, kalça
çevresi, bel/boy oranı, TKİ, BRI ve AVİ kullanılabilir.

Anahtar Kelimeler

Çocuklar, adölesanlar, antropometri, vücut kompozisyonu, vücut yağ yüzdesi

Etik Beyan

Ordu Üniversitesi, Klinik Araştırmalar Etik Kurulu’ndan onay alınmıştır (Karar Numarası: 2023/176).

Destekleyen Kurum

Yazarlar herhangi bir finansal destek alınmadığını beyan etmektedirler.

Teşekkür

Araştırmaya katılmaya gönüllü olan olgulara ve ailelerine teşekkür ederiz.

Kaynakça

• 1. GBD 2015 Obesity Collaborators; Afshin A, Forouzanfar MH, Reitsma MB, Sur P, Estep K, Lee A, Marczak L, Mokdad AH, Moradi-Lakeh M, Naghavi M, Salama JS, Vos T, Abate KH, Abbafati C, et al. Health Effects of Overweight and Obesity in 195 Countries over 25 Years. N Engl J Med. 2017;377(1):13-27.
• 2. Smith JD, Fu E, Kobayashi MA. Prevention and Management of Childhood Obesity and Its Psychological and Health Comorbidities. Annu Rev Clin Psychol. 2020;16:351-378.
• 3. Alper Z, Ercan İ, Uncu Y. A meta-analysis and an evaluation of trends in obesity prevalence among children and adolescents in Turkey: 1990 through 2015. JCRPE Journal of Clinical Research in Pediatric Endocrinology. 2018;10(1):59-67.
• 4. Van Eyck A, Eerens S, Trouet D, Lauwers E, Wouters K, De Winter BY, van der Lee JH, Van Hoeck K, Ledeganck KJ. Body composition monitoring in children and adolescents: reproducibility and reference values. Eur J Pediatr. 2021;180(6):1721- 1732.
• 5. Kuriyan R. Body composition techniques. Indian J Med Res. 2018;148(5):648-658.
• 6. Calella P, Gallè F, Fornelli G, Liguori G, Valerio G. Type 1 diabetes and body composition in youth: A systematic review. Diabetes Metab Res Rev. 2020;36(1):e3211.
• 7. Ghouili H, Ouerghi N, Ben Khalifa W, Boughalmi A, Dridi A, Gmada N, Bouassida A. First reference curves of waist circumference and waist-to-height ratio for Tunisian children. Arch Pediatr. 2020;27(2):87-94.
• 8. Alves Junior CA, Mocellin MC, Gonçalves ECA, Silva DA, Trindade EB. Anthropometric Indicators as Body Fat Discriminators in Children and Adolescents: A Systematic Review and Meta-Analysis. Adv Nutr. 2017;8(5):718-727.
• 9. Chula de Castro JA, Lima TR de, Silva DAS. Body composition estimation in children and adolescents by bioelectrical impedance analysis: A systematic review. J Bodyw Mov Ther. 2018;22(1):134-146.
• 10. Chen R, Ji L, Chen Y, Meng L. Weight-to-height ratio and body roundness index are superior indicators to assess cardio- metabolic risks in Chinese children and adolescents: compared with body mass index and a body shape index. Transl Pediatr. 2022;11(3):318-329.
• 11. McGraw MB, Kohler LN, Shaibi GQ, Mandarino LJ, Coletta DK. A performance review of novel adiposity indices for assessing insulin resistance in a pediatric Latino population. Front Pediatr. 2022;10:1020901.
• 12. Asif M, Aslam M, Altaf S. Evaluation of anthropometric parameters of central obesity in Pakistani children aged 5-12 years, using receiver operating characteristic (ROC) analysis. J Pediatr Endocrinol Metab. 2018;31(9):971-977.
• 13. Güngör NK. Overweight and obesity in children and adolescents. J Clin Res Pediatr Endocrinol. 2014;6(3):129-143.
• 14. Thivel D, Verney J, Miguet M, Masurier J, Cardenoux C, Lambert C, Courteix D, Metz L, Pereira B. The accuracy of bioelectrical impedance to track body composition changes depends on the degree of obesity in adolescents with obesity. Nutr Res. 2018;54:60-68.
• 15. Verney J, Metz L, Chaplais E, Cardenoux C, Pereira B, Thivel D. Bioelectrical impedance is an accurate method to assess body composition in obese but not severely obese adolescents. Nutrition Research [Internet]. 2016;36(7):663-670.
• 16. Kurtoglu S, Mazicioglu MM, Ozturk A, Hatipoglu N, Cicek B, Ustunbas HB. Body fat reference curves for healthy Turkish children and adolescents. Eur J Pediatr. 2010;169(11):1329- 1335.
• 17. Wang X, Ma J, Huang S, Dong B, Dong Y, Yang Z, Hu J, Liang W. Use of Tri-Ponderal Mass Index in Predicting Late Adolescent Overweight and Obesity in Children Aged 7-18. Front Nutr. 2022;9:785863.
• 18. Gómez-Ambrosi J, Silva C, Galofré JC, Escalada J, Santos S, Millán D, Vila N, Ibañez P, Gil MJ, Valentí V, Rotellar F, Ramírez B, Salvador J, Frühbeck G. Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity. Int J Obes (Lond). 2012;36(2):286- 294.
• 19. Peterson CM, Su H, Thomas DM, Heo M, Golnabi AH, Pietrobelli A, Heymsfield SB. Tri-Ponderal Mass Index vs Body Mass Index in Estimating Body Fat During Adolescence. JAMA Pediatr. 2017;171(7):629-636.
• 20. De Lorenzo A, Romano L, Di Renzo L, Gualtieri P, Salimei C, Carrano E, Rampello T, de Miranda RC. Triponderal mass index rather than body mass index: An indicator of high adiposity in Italian children and adolescents. Nutrition. 2019;60:41- 47.
• 21. Ye XF, Dong W, Tan LL, Zhang ZR, Qiu YL, Zhang J. Identification of the most appropriate existing anthropometric index for home-based obesity screening in children and adolescents. Public Health. 2020;189:20-25.
• 22. Özyildirim C, Unsal EN, Ayhan NY. Performance of triponderal mass index, body mass index z scores, and body mass index performance in the diagnosis of obesity in children and adolescents. Nutrition. 2023;114:112116.
• 23. Sun J, Yang R, Zhao M, Bovet P, Xi B. Tri-Ponderal Mass Index as a Screening Tool for Identifying Body Fat and Cardiovascular Risk Factors in Children and Adolescents: A Systematic Review. Front Endocrinol (Lausanne). 2021;12:694681.
• 24. De Santis Filgueiras M, Cecon RS, de Faria ER, de Faria FR, Pereira PF, Ribeiro AQ, Priore SE, de Novaes JF. Agreement of body adiposity index (BAI) and paediatric body adiposity index (BAIp) in determining body fat in Brazilian children and adolescents. Public Health Nutr. 2019;22(1):132-139.
• 25. Thivel D, O’Malley G, Pereira B, Duché P, Aucouturier J. Comparison of total body and abdominal adiposity indexes to dual x-ray absorptiometry scan in obese adolescents. Am J Hum Biol. 2015;27(3):334-338.
• 26. El Aarbaoui T, Samouda H, Zitouni D, di Pompeo C, de Beaufort C, Trincaretto F, Mormentyn A, Hubert H, Lemdani M, Guinhouya BC. Does the body adiposity index (BAI) apply to paediatric populations? Ann Hum Biol. 2013;40(5):451-458.
• 27. Colley D, Cines B, Current N, Schulman C, Bernstein S, Courville AB, Zambell K, Reynolds JC, Yanovski J. Assessing Body Fatness in Obese Adolescents: Alternative Methods to Dual-Energy X-Ray Absorptiometry. Digest (Wash DC). 2015;50(3):1- 7.
• 28. Dias IB, Panazzolo DG, Marques MF, Paredes BD, Souza MG, Manhanini DP, Morandi V, Farinatti PT, Bouskela E, Kraemer-Aguiar LG. Relationships between emerging cardiovascular risk factors, z-BMI, waist circumference and body adiposity index (BAI) on adolescents. Clin Endocrinol (Oxf). 2013;79(5):667-674.
• 29. Segheto W, Coelho FA, Cristina Guimarães da Silva D, Hallal PC, Marins JC, Ribeiro AQ, Pessoa MC, Morais SH, Longo GZ. Validity of body adiposity index in predicting body fat in Brazilians adults. Am J Hum Biol. 2017;29(1).
• 30. Morais NS, Miranda VPN, Ribeiro SAV, Pereira PF, de Souza ECG, Franceschini SDCC, Priore SE. Predictive capacity and cut-off points of adiposity indices for body fat prediction according to adolescent periods. Br J Nutr. 2021;126(11):1673- 1681.
• 31. Del Moral-Trinidad LE, Romo-González T, Carmona Figueroa YP, Barranca Enríquez A, Palmeros Exsome C, Campos- Uscanga Y. Potential for body mass index as a tool to estimate body fat in young people. Enfermeria clinica (English Edition). 2021;31(2):99-106.
• 32. Ismail NA, Ragab SH, El Baky AMNEDA, Ibrahim MH. Potential Role of New Anthropometric Parameters in Childhood Obesity with or Without Metabolic Syndrome. Open Access Maced J Med Sci. 2019;7(23):3930-3936.
• 33. Xu Y, Yan W, Cheung YB. Body shape indices and cardiometabolic risk in adolescents. Ann Hum Biol. 2015;42(1):70-75.
• 34. Lek N, Yan W, Zhang Y, Wang Q, Cheung YB. Indices of central and general obesity and cardiometabolic risk among adolescents in three ethnic groups in north-west China. Ann Hum Biol. 2016;43(1):18-24.
• 35. Perona JS, Schmidt Rio-Valle J, Ramírez-Vélez R, Correa-Rodríguez M, Fernández-Aparicio Á, González-Jiménez E. Waist circumference and abdominal volume index are the strongest anthropometric discriminators of metabolic syndrome in Spanish adolescents. Eur J Clin Invest. 2019;49(3):e13060.
• 36. Pérez B, Landaeta-Jiménez M, Vásquez M. [Adiposity distribution in adolescents by conicity index]. Acta Cient Venez. 2000;51(4):244-251.
• 37. Taylor RW, Jones IE, Williams SM, Goulding A. Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual- energy X-ray absorptiometry, in children aged 3-19 y. Am J Clin Nutr. 2000;72(2):490-495.